Systemic accident risk assessment in air traffic by Monte Carlo simulation

Abstract

A systemic accident model considers accidents as emergent phenomena from variability and interactions in a complex system. Air traffic risk assessments have predominantly been done by sequential and epidemiological accident models. In this paper we demonstrate that Monte Carlo simulation of safety relevant air traffic scenarios is a viable approach for systemic accident assessment. The Monte Carlo simulations are based on dynamic multi-agent models, which represent the distributed and dynamic interactions of various human operators and technical systems in a safety relevant scenario. The approach is illustrated for a particular runway incursion scenario, which addresses an aircraft taxiing towards the crossing of an active runway while its crew has inappropriate situation awareness. An assessment of the risk of a collision between the aircraft taxiing with an aircraft taking-off is presented, which is based on dedicated Monte Carlo simulations in combination with a validation approach of the simulation results. The assessment particularly focuses on the effectiveness of a runway incursion alert system that warns an air traffic controller, in reducing the safety risk for good and reduced visibility conditions.